The advent of electronic commerce (e-commerce) is forcing radical changes to the landscape of marketing and customer care. E-commerce customers are demanding increased flexibility and convenience in accessing on-line information about products, in ordering them, and obtaining service for them. At the same time, e-commerce businesses are attempting to support: (a) personalized marketing and service to large masses of people, including intelligent targeted advertising, and intelligent mechanisms to identify and take advantage of profitable and loyal customers; and (b) meaningful dialogues with customers so that quality of service can be improved before customers switch to a competitor. These needs are not restricted to “business-to-customer” (B2C) e-commerce web sites. Web sites in “business-to-business” (B2B) e-commerce that are accessed by employees of a business must also provide effective, personalized service.
In response, some e-commerce sites have proposed the use of rule-based mechanisms to assist in addressing the needs of participants, as well as their own needs, in personalizing their e-commerce applications to particular users. However, existing e-commerce personalization tools that utilize such rule-based mechanisms typically use rule languages that are quite limited.
For example, iContact (from !hey Inc. of North Andover, Mass.) uses a simple rules mechanism to identify customer sessions in an e-commerce application that are “good” candidates for live customer service representative (CSR) assistance. However, with iContact, the CSRs are given a listing of these candidates, and the CSRs make the final decision about whether or not to offer live intervention. Thus, with such an arrangement, the decision is made by a human operator. The iContact system, as with other existing approaches, also do not provide automated mechanisms for offering discounts or other options to customers.
In addition to e-commerce applications, existing interactive voice response (IVR) systems suffer from similar problems. That is, existing IVR systems do not provide automated mechanisms for evaluating the progress of a customer through an IVR sequence and then deciding whether to intervene by offering live assistance, discounts, or other options to the customer.
Still further, one may generally view existing workflow systems as suffering from analogous problems. As is known, a workflow system is a computer system which dictates how various classes of objects should be handled. Objects may include, for example, an incoming call to a call center, insurance claims arriving at a claim center, request for information from a web site, etc. As such, web servers that implement e-commerce applications and computer systems that implement IVR systems may be thought of as examples of workflow systems.
Thus, there is a need for techniques for use in accordance with such systems as e-commerce applications, IVR systems and workflow systems which provide automated monitoring of user activity and personalized action taking based on such activity, in accordance with a decision support mechanism.